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Landslide prediction method, device and equipment and storage medium

A prediction method and prediction model technology, applied in prediction, neural learning method, biological neural network model, etc., can solve the problems of many landslide influencing factors and poor prediction efficiency, so as to reduce the false alarm rate and false alarm rate, improve the The effect of prediction accuracy

Pending Publication Date: 2021-03-19
杭州鲁尔物联科技有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, there are many factors affecting landslides, and only one non-deterministic method is used for prediction, and the prediction efficiency is poor

Method used

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  • Landslide prediction method, device and equipment and storage medium
  • Landslide prediction method, device and equipment and storage medium
  • Landslide prediction method, device and equipment and storage medium

Examples

Experimental program
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Effect test

Embodiment 1

[0027] figure 1 It is a flow chart of a landslide prediction method provided by Embodiment 1 of the present invention. This embodiment is applicable to the situation of evaluating the susceptibility of landslides. The method can be executed by a landslide prediction device, such as figure 1 As shown, the method includes the following steps:

[0028] S110. Acquiring daily landslide impact factors within a set period of time for each slope unit in the target area.

[0029] Among them, the target area is usually the area where the landslide has occurred, and it can also be any designated area. The slope unit is the basic unit for the development of geological hazards such as landslides and collapses, and each unit is given a corresponding attribute value to represent a data form of the entity. The set time period may be one day, three days, one week, one month or other time periods before the day when the landslide occurs.

[0030] Wherein, the landslide impact factors include...

Embodiment 2

[0043] figure 2 It is a flow chart of a landslide prediction method provided by Embodiment 2 of the present invention. This embodiment is a further refinement of the previous embodiment. The landslide prediction method provided by this embodiment also includes: determining the impact of the landslide Whether the change value of the factor within the set time period exceeds the preset change threshold; if yes, the landslide influencing factor is determined as the dynamic factor, otherwise, the landslide influencing factor is determined as the static factor. For the parts not described in detail in the method embodiment, please refer to the above embodiment. For details, see figure 2 As shown, the method may include the following steps:

[0044] S210. Acquiring daily landslide impact factors within a set period of time for each slope unit in the target area.

[0045] Wherein, the landslide impact factors include dynamic factors and static factors.

[0046] S220. Determine ...

Embodiment 3

[0058] Figure 4 A schematic diagram of the results of a landslide prediction device provided in Embodiment 3 of the present invention, such as Figure 4 Said, the landslide prediction device includes: a landslide impact factor acquisition module 310 , a dynamic probability value determination module 320 , a static probability value determination module 330 and a landslide occurrence probability determination module 340 .

[0059] Wherein, the landslide impact factor acquisition module 310 is used to acquire the daily landslide impact factor within the set time period of each slope unit in the target area, wherein the landslide impact factor includes dynamic factors and static factors;

[0060] A dynamic probability value determination module 320, configured to determine the dynamic probability value of landslides in each slope unit based on the dynamic factors;

[0061] A static probability value determining module 330, configured to determine the static probability value of...

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Abstract

The embodiment of the invention discloses a landslide prediction method and device, equipment and a storage medium. The method comprises the following steps: obtaining landslide influence factors of each slope unit in a target area every day in a set time period, wherein the landslide influence factors comprise a dynamic factor and a static factor; determining a dynamic probability value of landslide of each slope unit based on the dynamic factors; and determining a static probability value of landslide of each slope unit based on the static factor, and separately performing landslide prediction on the dynamic factor and the static factor, so that the missing report rate and the false alarm rate in the landslide prediction process can be reduced. The landslide occurrence probability of thetarget area is obtained according to the dynamic probability value and the static probability value, the corresponding probability values of the two types of landslide influence factors are integrated for combined prediction, landslide prediction is carried out by combining the characteristics of the two types of landslide influence factors, and the prediction precision of landslide can be further improved.

Description

technical field [0001] The embodiments of the present invention relate to the technical field of landslide monitoring, in particular to a landslide prediction method, device, equipment and storage medium. Background technique [0002] Landslides are one of the most common catastrophic natural disasters, which have the characteristics of wide distribution, high frequency of occurrence, multiple, regional and serious, because landslides cause a large number of casualties and major environmental and infrastructure damage every year loss. It is of great significance to evaluate the susceptibility of landslides. [0003] The existing landslide susceptibility prediction can be divided into deterministic methods and non-deterministic methods according to the difference of their theoretical basis. Deterministic methods are mainly directional analysis based on expert experience and knowledge and methods based on landslide process or physical models, and the prediction accuracy is p...

Claims

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Application Information

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IPC IPC(8): G06Q10/04G06N3/08G06N3/04G06N20/20
CPCG06Q10/04G06N3/08G06N20/20G06N3/047G06N3/045
Inventor 张军郑增容商琪江子君宋杰胡辉
Owner 杭州鲁尔物联科技有限公司
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